Motor imagery and direct brain-computer communication

2001/07/01 by G. Pfurtscheller, C. Neuper, Christa Neuper · 1,956 citations
Engineering · Neuroscience · Psychology · #Advanced Memory and Neural Computing #Artificial intelligence #Brain activity and meditation #Brain–computer interface #Classifier (UML) #Computer science #EEG and Brain-Computer Interfaces #Electroencephalography #Motor imagery #Neuroscience #Neuroscience and Neural Engineering #Psychology #Set (abstract data type) #Speech recognition

paper · doi:10.1109/5.939829

published in Proceedings of the IEEE 89(7), 1123-1134 (Institute of Electrical and Electronics Engineers)

openalex publication_date 2001/07/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29

Abstract

Motor imagery can modify the neuronal activity in the primary sensorimotor areas in a very similar way as observable with a real executed movement. One part of EEG-based brain-computer interfaces (BCI) is based on the recording and classification of circumscribed and transient EEG changes during different types of motor imagery such as, e.g., imagination of left-hand, right-hand, or foot movement. Features such as, e.g., band power or adaptive autoregressive parameters are either extracted in bipolar EEG recordings overlaying sensorimotor areas or from an array of electrodes located over central and neighboring areas. For the classification of the features, linear discrimination analysis and neural networks are used. Characteristic for the Graz BCI is that a classifier is set up in a learning session and updated after one or more sessions with online feedback using the procedure of "rapid prototyping." As a result, a discrimination of two brain states (e.g., leftversus right-hand movement imagination) can be reached within only a few days of training. At this time, a tetraplegic patient is able to operate an EEG-based control of a hand orthosis with nearly 100% classification accuracy by mental imagination of specific motor commands.

Citations

• The Utah Intracortical Electrode Array: A recording structure for potential brain-computer interfaces
• EEG-based discrimination between imagination of right and left hand movement
• Post-movement beta synchronization. A correlate of an idling motor area?
• Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials
• A tutorial on hidden Markov models and selected applications in speech recognition

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• Longitudinal Analysis of Stroke Patients' Brain Rhythms during an Intervention with a Brain-Computer Interface. [europepmc]
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